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Enable Biosciences, Stanford to Develop Type 1 Diabetes Spit Test for Kids Under JDRF Grant

NEW YORK (GenomeWeb) – JDRF, a global organization funding type 1 diabetes (T1D) research, has awarded a grant to Stanford University to develop screening tests for T1D in children.

Under the two-year, $700,000 award, Stanford’s division of pediatric endocrinology and diabetes will work with Enable Biosciences, a UC Berkeley and Stanford StartX diagnostic company, to validate and expand the capability of Enable's antibody detection by agglutination-PCR (ADAP) assay platform for diagnosing T1D.

The test will specifically be geared toward pediatric screening. About 80 percent of children diagnosed with T1D have no family history or known genetic predisposition, Enable noted in a statement, and while other biomarker tests exist, they are too expensive and costly for screening.

"JDRF is excited about the potential of the Enable technology to detect autoantibodies in a small amount of saliva or blood," Jessica Dunne, JDRF's director of research said. "Prevention is a vital part of JDRF's mission to cure, prevent and treat type 1 diabetes, and an assay like this could remove obstacles and serve as a critical step toward being able to screen all kids for risk of T1D."

The ADAP method takes advantage of antibodies in patient samples to bring DNA strands together for PCR. Antigen proteins are chemically conjugated to PCR-incompetent half-amplicons, and if an antibody is present in a sample it will bind at least two antigens which can then be ligated and quantified with real-time PCR.

The award will fund efforts to further refine and validate an existing ADAP-based diabetes test with new samples collected from Stanford hospital. It will also fund comparisons of the ADAP test using serum and saliva in an effort to develop a T1D spit test for screening use.

Enable has previously been awarded funding from the National Institutes of Diabetes and Digestive and Kidney Diseases to develop an assay for T1D using the ADAP method and to perform retrospective analyses of pre-diabetic samples to determine if the technology can be used to detect biomarkers, such as autoantibodies to insulin producing cells in the pancreas, early in the disease process.